Knowledge-based public service transactions: An intelligent model-driven approach in co-learning contexts

Public administrations pursue the efficiency and quality of administrative services they offer as well as the reduction of time and operational costs in executing service transactions. However, some issues arise when trying to achieve these goals: (a) the lack of procedure formalization to describe public services, (b) a mechanism to guarantee services' obligatory compliance with frequently changing legal regulations, and (c) the efficient deployment of service transactions in e-government platforms. The aim of this work is to identify the phases of the development cycle of eGovernment transactions and provide the support to automatize them efficiently by using a model driven engineering (MDE) and knowledge-based approach. The main source of the knowledge extraction process comes from a collaborative learning environment where public servants share acquired domain knowledge. A web survey has been conducted to evaluate the approach acceptance degree by software developers and domain experts. The main conclusion is that 61% of the surveyed experts strongly agree that our approach improves actual eGovernment transactions practices and the phases needed to develop them.